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All Journal Jurnal Teknologi Informasi dan Ilmu Komputer Computatio : Journal of Computer Science and Information Systems Journal of Economic, Bussines and Accounting (COSTING) SAINTEK: Jurnal ilmiah Sains dan Teknologi Industri JURNAL LENTERA BISNIS Daengku: Journal of Humanities and Social Sciences Innovation Jurnal Algoritma Abdimas Indonesian Journal Journal of Artificial Intelligence and Digital Business Indonesian Journal of Community Empowerment (IJCE) Journal of Economics and Management Scienties Journal of Innovative and Creativity Jurnal Ilmiah Bisnis, Manajemen, dan Akuntansi Jurnal Bakti Humaniora Jurnal Informatika dan Kesehatan
Eko Nur Hermansyah
Universitas Ngudi Waluyo
Religion Humanities Chemistry Computer Science & IT Decision Sciences, Operations Research & Management Economics, Econometrics & Finance Education Electrical & Electronics Engineering Engineering Health Professions Industrial & Manufacturing Engineering Languange, Linguistic, Communication & Media Law, Crime, Criminology & Criminal Justice Library & Information Science Mathematics Medicine & Pharmacology Public Health Social Sciences Other

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Analisis Sentimen Ulasan Penggunaan Aplikasi GetContact Menggunakan Orange Data Mining sebagai Dasar Strategi Peningkatan Kualitas Layanan Isnatun Naili; Eko Nur Hermansyah
Jurnal Informatika dan Kesehatan Vol. 3 No. 2 (2026): IKN : Jurnal Informatika dan Kesehatan
Publisher : Universitas Ngudi Waluyo

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.35473/ikn.v3i2.5563

Abstract

The growth of phone number identification applications drives companies to continuously improve service quality to meet user needs and expectations. User reviews available on the Google Play Store serve as a valuable source of information for evaluating service quality. This study aims to analyze the sentiment of user reviews for the GetContact application to inform strategies for enhancing service quality. The dataset, obtained publicly from Kaggle, comprises 1,000 user reviews of the GetContact application. Analysis was conducted using Orange Data Mining, involving stages such as text preprocessing, word cloud visualization, and sentiment categorization. Sentiment labels were assigned based on user ratings: ratings of 1–2 indicated negative sentiment, a rating of 3 indicated neutral sentiment, and ratings of 4–5 indicated positive sentiment. The results show that 49.50% of the reviews reflected positive sentiment, 40.60% reflected negative sentiment, and 9.90% reflected neutral sentiment. Word cloud visualization revealed that words such as "helpful," "app," "number," and "update" frequently appeared in reviews containing complaints. These findings indicate that while the majority of users responded positively to the application's core functionality, the company still needs to improve service quality—specifically regarding system stability, the authentication process, and the development of premium features. The study's findings are expected to assist the company in formulating strategies to enhance service quality and customer satisfaction.   ABSTRAK Perkembangan aplikas identifikasi nomor telpon mendorong perusahaan untuk terus meningkatkan kualitas layanan agar mampu memenuhi kebutuhan dan harapan pengguna.salah satu sumber informasi yang dimanfaatkan untuk mengevaluasi kualitas layanan adalah ulasan pengguna yang tersedia pada Google Play Store. Penelitian ini bertujuan untuk menganalisis sentimen ulasan pengguna aplikasi GetContact sebagai sumber dalam penyusunan strategi peningkatan kualitas layanan. Data set yang merupakan dataset publik yang di peroleh dari kaggle, terdiri atas 1.000 ulasan pengguna aplikasi GetContact. Proses analisis dilakukan menggunakan orange data mining melalui tahapan text preprocessing, visualisasi word cloud, dan pengelompokan sentimen. Label sentimen dibentuk berdasarkan nilai rating pengguna, yaitu rating 1-2 sebagai sentimen negatif, reting 3 sebagai sentimen netral, dan 4-5 sebagai sentimen positif. Hasil penelitian menunjukkan bahwa 49,50 % ulasan termasuk sentimen positif. Hasil penelitian menunjukkan bahwa 4,9 50 % ulasan termasuk sentimen positif, 40,60% sentimen negatif, dan 9,90% sentimen netral. Visualisasi word cloud menunjukkan bahwa kata kata seperti membantu, aplikasi, nomor, dan update banyak muncul pada ulasan yang mengandung keluhan. Temua ini menunjukkan bahwa meskipun mayoritas pengguna memberikan tanggapan positif terhadap fungsi utama aplikasi, perusahaan tetap perlu meningkatkan kualitas layanan, khususnya pada aspek stablilitas sistem, proses autentikasi, dan pengembangan fitur preium. Hasil penelitian diharapkan dapat menjadi bahan pertimbangan bagi perusahaan dalam merumuskan strategi peningktana kualitas layanan dan kepuasan pelanggan.  
Co-Authors Abdul Aziz Abdul Aziz Ade Iriani Adi Purwanto Afnina Agung Mufti Wibowo Agung Wibowo Agus Surya Bharmawan Anwar S. Ardjo Anwar S. Ardjo, Anwar S. Ari Siswati Ari Siswati Arief Andriono Arief Andriono, Arief Arlin Reza Firnandita Caksana Setyo Widyatmoko Danny Manongga Diva Riyandini Eko Sediyono Elvira M. Usulu Erni Junaida Fatmasari, Ria Kristia Feby Arma Putra Firdaus Dwi Prasetyo Firdaus Dwi Prasetyo, Firdaus Dwi Firman Aziz Gizka Alysah Diva Haribowo, Rio I Nengah Suarmanayasa Ibnu Putra Surya Daru Irdiana, Sukma Irsal Fauzi Isnatun Naili Itot Bian Raharjo Jamaluddin Majid Jaya Ramadaey Bangsa Joyo Minardo Kustiyono Lailatul Fadhila Made Susilawati Menhard, Menhard Musta'in, Mukhammad N.A. Miftahul Huda N.A. Miftahul Huda, N.A. Miftahul ningrum, dedah - Nurnaningsih, Rita Olif Rina Susanti5 Prieza Dheva Tanti Ratna Sari Handayani Riesna Apramilda Rifka Dea Safitri Setya Indah Isnawati Setya Indah Isnawati Siswati, Ari Siti Rahayu Sri Purwati Sugiarto, Heri Syah Amin Albadry Trisna Wonda Trisna Wonda, Trisna Ulfamiyati Wahyuni Sri Astutik Zurlina Lubis